TsoukMon Viewer: Pokemon, Moves, and Abilities

Pokemon

Pokemon

Moves

Moves

Abilities

Abilities

# Pokemon Summary
poke_filter <- filter(poke_db, Name == "Geodude")
#poke_filter

#################
# Base Stats
poke_filter_base <- select(poke_filter, Name, Types, HP, ATTACK, DEFENSE, SPECIAL_ATTACK, SPECIAL_DEFENSE, SPEED, Abilities, HiddenAbilities, Evolutions)

selected_poke_stats <- gather(poke_filter_base, key = "Pokemon_ID", value = "Stat")
colnames(selected_poke_stats) <- c("Stat","Value")

#################
# Ability
ability_filter <- select(poke_filter,Pokemon_ID,Abilities,HiddenAbilities)
ability_filter <- ability_filter %>% separate(Abilities, into = c("Ability1", "Ability2"), sep = ",", fill = "right")
ability_filter <- ability_filter %>% separate(HiddenAbilities, into = c("HiddenAbility1","HiddenAbility2","HiddenAbility3"), sep = ",", fill = "right")
ability_end <- gather(ability_filter, key="Pokemon_ID", value = "Ability", na.rm = TRUE)

ability_list <- left_join(ability_end, ability_db, by = c("Ability" = "Ability_ID"))
colnames(ability_list) <- c(" ","Ability_ID","Ability","Description","Flags")

selected_poke_abilities <- select(ability_list, Ability, Description, " ")
#ability_summary

#################
# Selected Pokemon Moves
# Split learned moves into vector
elements <- unlist(strsplit(poke_filter$Moves, ","))
# Extract levels and moves (odd vs even indexed values)
levels <- as.integer(elements[c(TRUE, FALSE)]) # Odd-indexed values
moves <- elements[c(FALSE, TRUE)]              # Even-indexed values

# Create the data frame
moves_df <- data.frame(Level = levels, Move = moves, stringsAsFactors = FALSE)
selected_poke_moves <- left_join(moves_df, move_db, by = c("Move" = "Move_ID"))[,1:8]
# Pokemon Summary
#poke_filter <- filter(poke_db, Name == "Geodude")
poke_filter <- poke_db

###################
#### Base Stats ###
###################
poke_filter_base <- select(poke_filter, Pokemon_ID, Name, FormName, Types, HP, ATTACK, DEFENSE, SPECIAL_ATTACK, SPECIAL_DEFENSE, SPEED, Abilities, HiddenAbilities, Evolutions, Moves)

selected_poke_stats <- pivot_longer(poke_filter_base
             ,cols = c("Types","HP","ATTACK","DEFENSE","SPECIAL_ATTACK","SPECIAL_DEFENSE","SPEED","Moves","Evolutions","Abilities","HiddenAbilities")
             ,names_to = "Stat"
             ,values_to = "Value"
             )

selected_poke_stats <- filter(selected_poke_stats,! Stat %in% c("Moves", "Abilities", "HiddenAbilities", "Evolutions"))
names(selected_poke_stats)[names(selected_poke_stats) == 'Name'] <- 'Pokemon'
#colnames(selected_poke_stats) <- c("Stat","Value")
#selected_poke_stats

###################
##### Ability ####
##################
ability_filter <- select(poke_filter,Pokemon_ID,Name,FormName,Abilities,HiddenAbilities)
ability_filter <- ability_filter %>% separate(Abilities, into = c("Ability1", "Ability2"), sep = ",", fill = "right")
ability_filter <- ability_filter %>% separate(HiddenAbilities, into = c("HiddenAbility1","HiddenAbility2","HiddenAbility3"), sep = ",", fill = "right")
#ability_end <- gather(ability_filter, key="Pokemon_ID", value = "Ability", na.rm = TRUE)

ability_end <- pivot_longer(ability_filter
             ,cols = c("Ability1","Ability2","HiddenAbility1","HiddenAbility2","HiddenAbility3")
             ,names_to = "Type"
             ,values_to = "Ability")

ability_list <- filter(left_join(ability_end, ability_db, by = c("Ability" = "Ability_ID")), !is.na(Ability))
colnames(ability_list) <- c("Pokemon_ID","Pokemon","FormName"," ","Ability","Name","Description","Flags")

selected_poke_abilities <- select(ability_list, Pokemon, Ability, Description, " ")
#ability_summary

###############################
### Selected Pokemon Moves ###
##############################
poke_filter_NA_RM <- filter(poke_filter, !is.na(Moves))
poke_filter_moves <- select(poke_filter_NA_RM, Pokemon_ID, Name, Moves)

# Step 1: Split the Moves column into separate rows based on commas
# Transform the data
poke_move_summary <- poke_filter_NA_RM %>%
  # Separate each value in the Moves column into individual rows
  separate_rows(Moves, sep = ",") %>%
  # Add a column with row numbers to distinguish between level and move names
  group_by(Name) %>%
  mutate(row_id = 2 * ceiling(row_number() / 2)) %>%
  # Use modulo to identify odd rows as move levels and even rows as move names
  mutate(category = ifelse(row_number() %% 2 == 1, "Move_Level", "Move_Name")) %>%
  # Pivot data so that Move_Level and Move_Name are in separate columns
  pivot_wider(names_from = category, values_from = Moves) %>%
  # Remove the row_id column and ungroup
  select(-row_id) %>%
  ungroup() %>%
  # Convert the Move_Level column to numeric (since it's character after splitting)
  mutate(Move_Level = as.integer(Move_Level)) %>%
  # Select relevant columns
  select(Pokemon_ID, Name, Move_Level, Move_Name)

# Remove duplicates
poke_move_summary <- unique(poke_move_summary)

selected_poke_moves <- left_join(poke_move_summary, move_db, by = c("Move_Name" = "Move_ID"))[,1:11]
colnames(selected_poke_moves) <- c("Pokemon_ID","Pokemon","Level","Move_ID","Name","Type","Category","Power","Accuracy","PP","Target")
filter(selected_poke_moves, Pokemon == "Tsoukinator")


filter(poke_move_summary, Name == "Abomasnow")
filter(poke_move_summary, Name == "Tsoukinator")

filter(poke_filter_NA_RM, Name == "Tsoukinator")
test <- data.frame(Name = poke_filter_NA_RM$Name, Moves = poke_filter_NA_RM$Moves)

tidy_moves <- test %>%
  # Separate each value in the Moves column into individual rows
  separate_rows(Moves, sep = ",") %>%
  # Add a column with row numbers to distinguish between level and move names
  group_by(Name) %>%
  mutate(row_id = 2 * ceiling(row_number()/2)) %>%
  # Use modulo to identify the odd rows as move levels and even rows as move names
  mutate(category = ifelse(row_id %% 2 == 1, "Move_Level", "Move_Name")) %>%
  # Pivot data so that Move_Level and Move_Name are in separate columns
  pivot_wider(names_from = category, values_from = Moves) %>%
  # Remove the row_id column and ungroup
  #select(-row_id) %>%
  ungroup()

tsouk <- filter(tidy_moves, Name == "Tsoukinator")

#2 * round(df$a/2)
t <- unlist(tsouk$Move_Name[[1]])
t
# Assuming you've already transformed the data as described
tidy_moves <- poke_filter_NA_RM %>%
  # Separate each value in the Moves column into individual rows
  separate_rows(Moves, sep = ",") %>%
  # Add a column with row numbers to distinguish between level and move names
  group_by(Name) %>%
  mutate(row_id = 2 * ceiling(row_number() / 2)) %>%
  # Use modulo to identify odd rows as move levels and even rows as move names
  mutate(category = ifelse(row_number() %% 2 == 1, "Move_Level", "Move_Name")) %>%
  # Pivot data so that Move_Level and Move_Name are in separate columns
  pivot_wider(names_from = category, values_from = Moves) %>%
  # Remove the row_id column and ungroup
  select(-row_id) %>%
  ungroup() %>%
  # Convert the Move_Level column to numeric (since it's character after splitting)
  mutate(Move_Level = as.integer(Move_Level)) %>%
  # Select relevant columns
  select(Pokemon_ID, Name, Move_Level, Move_Name)

# View the result
print(tidy_moves)


filter(tidy_moves, Name == "Tsoukinator")
tsoukmon_pkmn <- select(filter(readxl::read_excel("PokeDB.xlsx", sheet = "PkmnStats"), is.na(`Pokedex Number`)), Name)
tsoukmon_pkmn$Pokemon_ID <- toupper(gsub(" ","",tsoukmon_pkmn$Name))

tsoukmon_moves <- select(filter(readxl::read_excel("PokeDB.xlsx", sheet = "Moves")), Name)
tsoukmon_moves$Move_ID <- toupper(gsub(" ","",tsoukmon_moves$Name))

tsoukmon_abilities <- select(filter(readxl::read_excel("PokeDB.xlsx", sheet = "Abilities")), Name)
tsoukmon_abilities$Ability_ID <- toupper(gsub(" ","",tsoukmon_abilities$Name))

test <- filter(poke_db_short, (Name == "Tsoukinator" | Name == "Pikachu"))

test_join <- left_join(test, tsoukmon_pkmn, by = c("Name" = "Name"))
test_join

test$TsoukMon_OG <- test$Name %in% tsoukmon_pkmn$Name
library(plotly)
library(RColorBrewer)

palette_blues <- colorRampPalette(colors =c("#F34444","#FF7F0F","#FFDD57","#A0E515","#00C2B8"))

tsouk_colours <- c("#F34444","#FF7F0F","#FFDD57","#A0E515","#00C2B8")
tsouk_palette <- brewer.pal(n=5, name="Dark2")
tsouk_palette <- tsouk_palette
#val

foodbaby <- filter(selected_poke_stats, Pokemon == "FoodBaby" & Stat != "Types")
foodbaby$Stat <- factor(foodbaby$Stat, levels = c("HP", "ATTACK", "DEFENSE", "SPECIAL_ATTACK", "SPECIAL_DEFENSE", "SPEED"))

foodbaby$Value <- as.numeric(foodbaby$Value)
fig <- plot_ly(x = foodbaby$Value, y = foodbaby$Stat, type = 'bar', orientation = 'h',
               marker = list(color = brewer.pal(6, "Dark2")),
               text = foodbaby$Value,       # Show the Value as text
               textposition = 'auto') %>%
  layout(
    xaxis = list(range = c(0, 200),showticklabels = FALSE),
    yaxis = list(autorange = "reversed"
    ),
    height = 300
  )
Warning: Specifying width/height in layout() is now deprecated.
Please specify in ggplotly() or plot_ly()
fig



#brewer.pal(6, "Dark2")
library(plotly)

# Your custom color palette
tsouk_colours <- c("#F34444", "#FF7F0F", "#FFDD57", "#A0E515", "#00C2B8")

# Define breaks and corresponding colors
breaks <- c(-1, 40, 60, 90, 120, 200)
colors <- tsouk_colours

# Function to assign colors based on breaks
assign_color <- function(value) {
  cut(value, breaks = breaks, labels = colors, include.lowest = TRUE)
}

# Apply the color assignment function
value_colors <- assign_color(foodbaby$Value)

# Create the Plotly figure
fig <- plot_ly(x = foodbaby$Value, y = foodbaby$Stat, type = 'bar', orientation = 'h',
               marker = list(color = value_colors), # Use discrete colors
               text = foodbaby$Value,       # Show the Value as text
               textposition = 'auto') %>%
  layout(
    xaxis = list(range = c(0, 200), showticklabels = FALSE),
    yaxis = list(autorange = "reversed"),
    height = 300
  )
Warning: Specifying width/height in layout() is now deprecated.
Please specify in ggplotly() or plot_ly()
fig
NA
NA
# Load necessary library
library(plotly)
library(grDevices)

# Original color palette
tsouk_colours <- c("#F34444", "#FF7F0F", "#FFDD57", "#A0E515", "#00C2B8")

# Function to create a color scale with intermediate colors
create_color_scale <- function(colors, n) {
  # Interpolate colors
  color_scale <- colorRampPalette(colors)(n)
  return(color_scale)
}

# Create a new color scale with 10 colors
expanded_colours <- create_color_scale(tsouk_colours, 8)

# Define breaks (one more than the number of colors)
breaks <- c(-1, 0, 20, 40, 60, 80, 100, 150, 200)
colors <- expanded_colours  # Use the expanded color palette

# Function to assign colors based on breaks
assign_color <- function(value) {
  cut(value, breaks = breaks, labels = colors, include.lowest = TRUE)
}

base_stats <- filter(selected_poke_stats, Pokemon == "Haydos" & Stat != "Types")
base_stats$Stat <- factor(base_stats$Stat, levels = c("HP", "ATTACK", "DEFENSE", "SPECIAL_ATTACK", "SPECIAL_DEFENSE", "SPEED"))

base_stats$Value <- as.numeric(base_stats$Value)

# Apply the color assignment function
value_colors <- assign_color(base_stats$Value)

# Create the Plotly figure
fig <- plot_ly(x = base_stats$Value, y = base_stats$Stat, type = 'bar', orientation = 'h',
               marker = list(color = value_colors), # Use discrete colors
               text = base_stats$Value,       # Show the Value as text
               textposition = 'auto') %>%
  layout(
    xaxis = list(range = c(0, 200), showticklabels = FALSE, showgrid = FALSE),
    yaxis = list(autorange = "reversed"),
    height = 270,
    plot_bgcolor  = "transparent",
           paper_bgcolor = "transparent"
  )
Warning: Specifying width/height in layout() is now deprecated.
Please specify in ggplotly() or plot_ly()
fig
NA
---
title: "TsoukMon"
output: html_notebook
---

<style>
.main-container {
  max-width: 100% !important;
}
</style>

TsoukMon Viewer: Pokemon, Moves, and Abilities

```{r setup, include = FALSE}
# https://medium.com/@SportSciData/https-medium-com-collinsneil306-how-to-create-interactive-reports-with-r-markdown-part-i-4fa9df46cd9

#rm(list=ls()) # Clear workspace
library(data.table)
library(readxl)
library(dplyr)
library(readr)
library(rlist)
library(tidyr)
library(purrr)
library(stringr)
library(DT)

# Define the path to the folder where your files are located
file_path <- "../PBS/"

############################################################################
############################# MOVE LIST ####################################
############################################################################
# List all files in the folder that start with "pokemon" - but not pokemon metrics
move_files <- list.files(path = file_path, pattern = "^moves", full.names = TRUE)

# Read all the files using read_delim
move_data <- map(move_files, read_delim, delim = "\n", trim_ws = TRUE, col_names = FALSE)

# Combine the list of data frames into one data frame (if applicable)
movelist_txt <- bind_rows(move_data)

# Split on Equals sign
movelist_split <- data.frame(do.call('rbind', strsplit(as.character(movelist_txt$X1),'=',fixed=TRUE)))
movelist_split$X1 <- trimws(movelist_split$X1)
movelist_split$X2 <- trimws(movelist_split$X2)

##########################################
## Add Move Name to Moves
movelist_split_end <- movelist_split %>%
  mutate(Move_ID = ifelse(grepl("^\\[", X1), X1, NA)) %>%  # Extract rows where X1 starts with '['
  fill(Move_ID)                                            # Fill down the group name

# Remove Key Fields from data-frame
movelist_split_end <- filter(movelist_split_end, !grepl("^\\[", X1) & !grepl("^\\#---", X1) & !grepl("^\\#", X1))

# Explicitly specifying the key column 'Move_Name'
move_db <- pivot_wider(
  data = movelist_split_end,
  names_from = X1,  # Column whose values become column names
  values_from = X2, # Column whose values fill the table
  id_cols = c(Move_ID)  # Explicitly specifying the key column
)

# Remove square brackets from Move_ID column
move_db$Move_ID <- substr(move_db$Move_ID, 2, nchar(move_db$Move_ID) - 1)

move_db <- move_db[order(move_db$Move_ID),]
move_db_short <- move_db %>% select(Name, Type, Category, Power, Accuracy, TotalPP, Target, Description, EffectChance, Priority) 
############################################################################
############################# Pokemon LIST ####################################
############################################################################

# List all files in the folder that start with "pokemon" - but not pokemon metrics
pokemon_files <- list.files(path = file_path, pattern = "^pokemon", full.names = TRUE)
# Filter out files that contain "_metrics" in the name
pokemon_files <- pokemon_files[!grepl("_metrics", pokemon_files)]

# Read all the files using read_delim
pokemon_data <- map(pokemon_files, read_delim, delim = "\n", trim_ws = TRUE, col_names = FALSE)

# Combine the list of data frames into one data frame (if applicable)
pokelist_txt <- bind_rows(pokemon_data)

# Split on Equals sign
pokelist_split <- data.frame(do.call('rbind', strsplit(as.character(pokelist_txt$X1),'=',fixed=TRUE)))
pokelist_split$X1 <- trimws(pokelist_split$X1)
pokelist_split$X2 <- trimws(pokelist_split$X2)

##########################################
## Add Pokemon Name to each row
pokelist_split_end <- pokelist_split %>%
  mutate(Pokemon_ID = ifelse(grepl("^\\[", X1), X1, NA)) %>%  # Extract rows where X1 starts with '['
  fill(Pokemon_ID)                                         # Fill down the group name

# Assign ID order to existing Pokemon List, skipping the first row
setDT(pokelist_split_end)[-1, Pokedex_No := .GRP, by = Pokemon_ID]

# Remove Key Fields from data-frame
pokelist_split_end <- filter(pokelist_split_end, !grepl("^\\[", X1) & !grepl("^\\#---", X1) & !grepl("^\\#", X1))

# Summarize multiple key values by concatenating them
pokelist_split_end <- pokelist_split_end %>%
  group_by(Pokedex_No, Pokemon_ID, X1) %>%
  summarise(X2 = str_c(X2, collapse = ", "), .groups = "drop")

# Explicitly specifying the key column 'Move_Name'
poke_db <- pivot_wider(
  data = pokelist_split_end,
  names_from = X1,  # Column whose values become column names
  values_from = X2, # Column whose values fill the table
  id_cols = c(Pokedex_No, Pokemon_ID)  # Explicitly specifying the key column
)

# Remove square brackets from Move_ID column
poke_db$Pokemon_ID <- substr(poke_db$Pokemon_ID, 2, nchar(poke_db$Pokemon_ID) - 1)
# If Name is not present, replace with proper case ID (split prior to comma)
poke_db$Name <- ifelse(
  is.na(poke_db$Name), 
  str_to_title(sapply(str_split(poke_db$Pokemon_ID, ",", simplify = TRUE), function(x) x[1])),
  poke_db$Name
)

# If FormName is not present, replace with "Standard Form"
poke_db$FormName <- ifelse(is.na(poke_db$FormName),"Standard Form",poke_db$FormName)
# Split out base stats
poke_db <- poke_db %>%
  separate(BaseStats, into = c("HP", "ATTACK","DEFENSE","SPEED","SPECIAL_ATTACK","SPECIAL_DEFENSE"), sep = ",", fill = "right")

poke_db <- poke_db[order(poke_db$Pokedex_No),]
poke_db_short <- poke_db %>% select(Pokedex_No, Name, FormName, Types, HP, ATTACK, DEFENSE, SPECIAL_ATTACK, SPECIAL_DEFENSE, SPEED, Abilities, HiddenAbilities, Evolutions) 
############################################################################
############################# Abilities LIST ####################################
############################################################################

# List all files in the folder that start with "pokemon" - but not pokemon metrics
ability_files <- list.files(path = file_path, pattern = "^abilities", full.names = TRUE)
# Filter out files that contain "_metrics" in the name
ability_files <- ability_files[!grepl("_Innate", ability_files)]

# Read all the files using read_delim
ability_data <- map(ability_files, read_delim, delim = "\n", trim_ws = TRUE, col_names = FALSE)

# Combine the list of data frames into one data frame (if applicable)
abilitylist_txt <- bind_rows(ability_data)

# Split on Equals sign
abilitylist_split <- data.frame(do.call('rbind', strsplit(as.character(abilitylist_txt$X1),'=',fixed=TRUE)))
abilitylist_split$X1 <- trimws(abilitylist_split$X1)
abilitylist_split$X2 <- trimws(abilitylist_split$X2)

##########################################
## Add Move Name to Moves
abilitylist_split_end <- abilitylist_split %>%
  mutate(Ability_ID = ifelse(grepl("^\\[", X1), X1, NA)) %>%  # Extract rows where X1 starts with '['
  fill(Ability_ID)                                            # Fill down the group name

# Remove Key Fields from data-frame
abilitylist_split_end <- filter(abilitylist_split_end, !grepl("^\\[", X1) & !grepl("^\\#---", X1) & !grepl("^\\#", X1))

# Explicitly specifying the key column 'Ability_ID'
ability_db <- pivot_wider(
  data = abilitylist_split_end,
  names_from = X1,  # Column whose values become column names
  values_from = X2, # Column whose values fill the table
  id_cols = c(Ability_ID)  # Explicitly specifying the key column
)

# Remove square brackets from Move_ID column
ability_db$Ability_ID <- substr(ability_db$Ability_ID, 2, nchar(ability_db$Ability_ID) - 1)

ability_db <- ability_db[order(ability_db$Ability_ID),]

#ability_db_short <- ability_db %>% select(Name, FormName, Type, HP, ATTACK, DEFENSE, SPECIAL_ATTACK, SPECIAL_DEFENSE, SPEED, Abilities, HiddenAbilities, Evolutions) 

```

## {.tabset}

### Pokemon

Pokemon
```{r, echo = FALSE, warning=FALSE}
DT::datatable(poke_db_short, rownames = FALSE, filter = "top", class = 'cell-border stripe', extensions = 'Buttons', options = list(dom = 'Bfrtip', buttons = c('copy', 'csv', 'excel', 'pdf', 'print'), search = list(search = "")))  %>%
  DT::formatStyle(columns = c(1:ncol(poke_db)), fontSize = '80%')
```

### Moves
Moves
```{r, echo = FALSE}
DT::datatable(move_db_short, rownames = FALSE, filter = "top", class = 'cell-border stripe', extensions = 'Buttons', options = list(dom = 'Bfrtip', buttons = c('copy', 'csv', 'excel', 'pdf', 'print'), search = list(search = "")))  %>%
  DT::formatStyle(columns = c(1:ncol(move_db)), fontSize = '80%')

```

### Abilities
Abilities
```{r, echo = FALSE}
DT::datatable(ability_db, rownames = FALSE, filter = "top", class = 'cell-border stripe', extensions = 'Buttons', options = list(dom = 'Bfrtip', buttons = c('copy', 'csv', 'excel', 'pdf', 'print'), search = list(search = "")))  %>%
  DT::formatStyle(columns = c(1:ncol(ability_db)), fontSize = '80%')
```


```{r}
# Pokemon Summary
poke_filter <- filter(poke_db, Name == "Geodude")
#poke_filter

#################
# Base Stats
poke_filter_base <- select(poke_filter, Name, Types, HP, ATTACK, DEFENSE, SPECIAL_ATTACK, SPECIAL_DEFENSE, SPEED, Abilities, HiddenAbilities, Evolutions)

selected_poke_stats <- gather(poke_filter_base, key = "Pokemon_ID", value = "Stat")
colnames(selected_poke_stats) <- c("Stat","Value")

#################
# Ability
ability_filter <- select(poke_filter,Pokemon_ID,Abilities,HiddenAbilities)
ability_filter <- ability_filter %>% separate(Abilities, into = c("Ability1", "Ability2"), sep = ",", fill = "right")
ability_filter <- ability_filter %>% separate(HiddenAbilities, into = c("HiddenAbility1","HiddenAbility2","HiddenAbility3"), sep = ",", fill = "right")
ability_end <- gather(ability_filter, key="Pokemon_ID", value = "Ability", na.rm = TRUE)

ability_list <- left_join(ability_end, ability_db, by = c("Ability" = "Ability_ID"))
colnames(ability_list) <- c(" ","Ability_ID","Ability","Description","Flags")

selected_poke_abilities <- select(ability_list, Ability, Description, " ")
#ability_summary

#################
# Selected Pokemon Moves
# Split learned moves into vector
elements <- unlist(strsplit(poke_filter$Moves, ","))
# Extract levels and moves (odd vs even indexed values)
levels <- as.integer(elements[c(TRUE, FALSE)]) # Odd-indexed values
moves <- elements[c(FALSE, TRUE)]              # Even-indexed values

# Create the data frame
moves_df <- data.frame(Level = levels, Move = moves, stringsAsFactors = FALSE)
selected_poke_moves <- left_join(moves_df, move_db, by = c("Move" = "Move_ID"))[,1:8]

```
```{r}
# Pokemon Summary
#poke_filter <- filter(poke_db, Name == "Geodude")
poke_filter <- poke_db

###################
#### Base Stats ###
###################
poke_filter_base <- select(poke_filter, Pokemon_ID, Name, FormName, Types, HP, ATTACK, DEFENSE, SPECIAL_ATTACK, SPECIAL_DEFENSE, SPEED, Abilities, HiddenAbilities, Evolutions, Moves)

selected_poke_stats <- pivot_longer(poke_filter_base
             ,cols = c("Types","HP","ATTACK","DEFENSE","SPECIAL_ATTACK","SPECIAL_DEFENSE","SPEED","Moves","Evolutions","Abilities","HiddenAbilities")
             ,names_to = "Stat"
             ,values_to = "Value"
             )

selected_poke_stats <- filter(selected_poke_stats,! Stat %in% c("Moves", "Abilities", "HiddenAbilities", "Evolutions"))
names(selected_poke_stats)[names(selected_poke_stats) == 'Name'] <- 'Pokemon'
#colnames(selected_poke_stats) <- c("Stat","Value")
#selected_poke_stats

###################
##### Ability ####
##################
ability_filter <- select(poke_filter,Pokemon_ID,Name,FormName,Abilities,HiddenAbilities)
ability_filter <- ability_filter %>% separate(Abilities, into = c("Ability1", "Ability2"), sep = ",", fill = "right")
ability_filter <- ability_filter %>% separate(HiddenAbilities, into = c("HiddenAbility1","HiddenAbility2","HiddenAbility3"), sep = ",", fill = "right")
#ability_end <- gather(ability_filter, key="Pokemon_ID", value = "Ability", na.rm = TRUE)

ability_end <- pivot_longer(ability_filter
             ,cols = c("Ability1","Ability2","HiddenAbility1","HiddenAbility2","HiddenAbility3")
             ,names_to = "Type"
             ,values_to = "Ability")

ability_list <- filter(left_join(ability_end, ability_db, by = c("Ability" = "Ability_ID")), !is.na(Ability))
colnames(ability_list) <- c("Pokemon_ID","Pokemon","FormName"," ","Ability","Name","Description","Flags")

selected_poke_abilities <- select(ability_list, Pokemon, Ability, Description, " ")
#ability_summary

###############################
### Selected Pokemon Moves ###
##############################
poke_filter_NA_RM <- filter(poke_filter, !is.na(Moves))
poke_filter_moves <- select(poke_filter_NA_RM, Pokemon_ID, Name, Moves)

# Step 1: Split the Moves column into separate rows based on commas
# Transform the data
poke_move_summary <- poke_filter_NA_RM %>%
  # Separate each value in the Moves column into individual rows
  separate_rows(Moves, sep = ",") %>%
  # Add a column with row numbers to distinguish between level and move names
  group_by(Name) %>%
  mutate(row_id = 2 * ceiling(row_number() / 2)) %>%
  # Use modulo to identify odd rows as move levels and even rows as move names
  mutate(category = ifelse(row_number() %% 2 == 1, "Move_Level", "Move_Name")) %>%
  # Pivot data so that Move_Level and Move_Name are in separate columns
  pivot_wider(names_from = category, values_from = Moves) %>%
  # Remove the row_id column and ungroup
  select(-row_id) %>%
  ungroup() %>%
  # Convert the Move_Level column to numeric (since it's character after splitting)
  mutate(Move_Level = as.integer(Move_Level)) %>%
  # Select relevant columns
  select(Pokemon_ID, Name, Move_Level, Move_Name)

# Remove duplicates
poke_move_summary <- unique(poke_move_summary)

selected_poke_moves <- left_join(poke_move_summary, move_db, by = c("Move_Name" = "Move_ID"))[,1:11]
colnames(selected_poke_moves) <- c("Pokemon_ID","Pokemon","Level","Move_ID","Name","Type","Category","Power","Accuracy","PP","Target")
```

```{r}
filter(selected_poke_moves, Pokemon == "Tsoukinator")


filter(poke_move_summary, Name == "Abomasnow")
filter(poke_move_summary, Name == "Tsoukinator")

filter(poke_filter_NA_RM, Name == "Tsoukinator")
```

```{r}
test <- data.frame(Name = poke_filter_NA_RM$Name, Moves = poke_filter_NA_RM$Moves)

tidy_moves <- test %>%
  # Separate each value in the Moves column into individual rows
  separate_rows(Moves, sep = ",") %>%
  # Add a column with row numbers to distinguish between level and move names
  group_by(Name) %>%
  mutate(row_id = 2 * ceiling(row_number()/2)) %>%
  # Use modulo to identify the odd rows as move levels and even rows as move names
  mutate(category = ifelse(row_id %% 2 == 1, "Move_Level", "Move_Name")) %>%
  # Pivot data so that Move_Level and Move_Name are in separate columns
  pivot_wider(names_from = category, values_from = Moves) %>%
  # Remove the row_id column and ungroup
  #select(-row_id) %>%
  ungroup()

tsouk <- filter(tidy_moves, Name == "Tsoukinator")

#2 * round(df$a/2)
t <- unlist(tsouk$Move_Name[[1]])
t
```
```{r}
# Assuming you've already transformed the data as described
tidy_moves <- poke_filter_NA_RM %>%
  # Separate each value in the Moves column into individual rows
  separate_rows(Moves, sep = ",") %>%
  # Add a column with row numbers to distinguish between level and move names
  group_by(Name) %>%
  mutate(row_id = 2 * ceiling(row_number() / 2)) %>%
  # Use modulo to identify odd rows as move levels and even rows as move names
  mutate(category = ifelse(row_number() %% 2 == 1, "Move_Level", "Move_Name")) %>%
  # Pivot data so that Move_Level and Move_Name are in separate columns
  pivot_wider(names_from = category, values_from = Moves) %>%
  # Remove the row_id column and ungroup
  select(-row_id) %>%
  ungroup() %>%
  # Convert the Move_Level column to numeric (since it's character after splitting)
  mutate(Move_Level = as.integer(Move_Level)) %>%
  # Select relevant columns
  select(Pokemon_ID, Name, Move_Level, Move_Name)

# View the result
print(tidy_moves)


filter(tidy_moves, Name == "Tsoukinator")
```
```{r}
tsoukmon_pkmn <- select(filter(readxl::read_excel("PokeDB.xlsx", sheet = "PkmnStats"), is.na(`Pokedex Number`)), Name)
tsoukmon_pkmn$Pokemon_ID <- toupper(gsub(" ","",tsoukmon_pkmn$Name))

tsoukmon_moves <- select(filter(readxl::read_excel("PokeDB.xlsx", sheet = "Moves")), Name)
tsoukmon_moves$Move_ID <- toupper(gsub(" ","",tsoukmon_moves$Name))

tsoukmon_abilities <- select(filter(readxl::read_excel("PokeDB.xlsx", sheet = "Abilities")), Name)
tsoukmon_abilities$Ability_ID <- toupper(gsub(" ","",tsoukmon_abilities$Name))

test <- filter(poke_db_short, (Name == "Tsoukinator" | Name == "Pikachu"))

test_join <- left_join(test, tsoukmon_pkmn, by = c("Name" = "Name"))
test_join

test$TsoukMon_OG <- test$Name %in% tsoukmon_pkmn$Name
```

```{r}
library(plotly)
library(RColorBrewer)

palette_blues <- colorRampPalette(colors =c("#F34444","#FF7F0F","#FFDD57","#A0E515","#00C2B8"))

tsouk_colours <- c("#F34444","#FF7F0F","#FFDD57","#A0E515","#00C2B8")
tsouk_palette <- brewer.pal(n=5, name="Dark2")
tsouk_palette <- tsouk_palette
#val

foodbaby <- filter(selected_poke_stats, Pokemon == "FoodBaby" & Stat != "Types")
foodbaby$Stat <- factor(foodbaby$Stat, levels = c("HP", "ATTACK", "DEFENSE", "SPECIAL_ATTACK", "SPECIAL_DEFENSE", "SPEED"))

foodbaby$Value <- as.numeric(foodbaby$Value)
fig <- plot_ly(x = foodbaby$Value, y = foodbaby$Stat, type = 'bar', orientation = 'h',
               marker = list(color = brewer.pal(6, "Dark2")),
               text = foodbaby$Value,       # Show the Value as text
               textposition = 'auto') %>%
  layout(
    xaxis = list(range = c(0, 200),showticklabels = FALSE),
    yaxis = list(autorange = "reversed"
    ),
    height = 300
  )

fig



#brewer.pal(6, "Dark2")
```

```{r}
library(plotly)

# Your custom color palette
tsouk_colours <- c("#F34444", "#FF7F0F", "#FFDD57", "#A0E515", "#00C2B8")

# Define breaks and corresponding colors
breaks <- c(-1, 40, 60, 90, 120, 200)
colors <- tsouk_colours

# Function to assign colors based on breaks
assign_color <- function(value) {
  cut(value, breaks = breaks, labels = colors, include.lowest = TRUE)
}

# Apply the color assignment function
value_colors <- assign_color(foodbaby$Value)

# Create the Plotly figure
fig <- plot_ly(x = foodbaby$Value, y = foodbaby$Stat, type = 'bar', orientation = 'h',
               marker = list(color = value_colors), # Use discrete colors
               text = foodbaby$Value,       # Show the Value as text
               textposition = 'auto') %>%
  layout(
    xaxis = list(range = c(0, 200), showticklabels = FALSE),
    yaxis = list(autorange = "reversed"),
    height = 300
  )

fig


```

```{r}
# Load necessary library
library(plotly)
library(grDevices)

# Original color palette
tsouk_colours <- c("#F34444", "#FF7F0F", "#FFDD57", "#A0E515", "#00C2B8")

# Function to create a color scale with intermediate colors
create_color_scale <- function(colors, n) {
  # Interpolate colors
  color_scale <- colorRampPalette(colors)(n)
  return(color_scale)
}

# Create a new color scale with 10 colors
expanded_colours <- create_color_scale(tsouk_colours, 8)

# Define breaks (one more than the number of colors)
breaks <- c(-1, 0, 20, 40, 60, 80, 100, 150, 200)
colors <- expanded_colours  # Use the expanded color palette

# Function to assign colors based on breaks
assign_color <- function(value) {
  cut(value, breaks = breaks, labels = colors, include.lowest = TRUE)
}
```

```{r}

base_stats <- filter(selected_poke_stats, Pokemon == "Haydos" & Stat != "Types")
base_stats$Stat <- factor(base_stats$Stat, levels = c("HP", "ATTACK", "DEFENSE", "SPECIAL_ATTACK", "SPECIAL_DEFENSE", "SPEED"))

base_stats$Value <- as.numeric(base_stats$Value)

# Apply the color assignment function
value_colors <- assign_color(base_stats$Value)

# Create the Plotly figure
fig <- plot_ly(x = base_stats$Value, y = base_stats$Stat, type = 'bar', orientation = 'h',
               marker = list(color = value_colors), # Use discrete colors
               text = base_stats$Value,       # Show the Value as text
               textposition = 'auto') %>%
  layout(
    xaxis = list(range = c(0, 200), showticklabels = FALSE, showgrid = FALSE),
    yaxis = list(autorange = "reversed"),
    height = 270,
    plot_bgcolor  = "transparent",
           paper_bgcolor = "transparent"
  )

fig

```

